• Niveau d'étude

    BAC +5

  • ECTS

    4,5 crédits

  • Composante

    Sciences économiques, gestion, mathématiques et informatique

  • Volume horaire

    24h

  • Période de l'année

    Enseignement dixième semestre

Description

This seminar examines the frontier of contemporary finance, focusing on structural shifts that are reshaping how capital is raised, allocated, and priced globally. Each session combines academic research with current market developments, practitioner perspectives, and policy debates.

Students are expected to come prepared, lead discussions, and engage critically with the material.

Session 1 — Private Credit: Rise of the Shadow Banking System
Session 2 — Fintech, Crypto & Decentralised Finance
Session 3 — Sustainable Finance & ESG
Session 4 — Market Microstructure & Liquidity
Session 5 — Innovation Finance: Europe vs the United States
Session 6 — Private Equity & Venture Capital: Value Creation Beyond Capital
Session 7 — Macro Finance & Geopolitical Risk
Session 8 — AI & Risk Management

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Objectifs

The seminar is deliberately structured around unsettled questions — areas where the evidence is contested and the implications are still unfolding — to foster original thinking and rigorous analysis.

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Évaluation

Modalités : CCI
SESSION UNIQUE :
Contrôle Continu
• Type : Oral, Dossier
• Durée : --
• Précisions : Présentations orales et dossier

Régime Dérogatoire
• Type : Dossier
• Durée : --


SESSION 2 :
• Type : Dossier
• Durée : --

Utilisation de l'intelligence artificielle : 
AI tools (e.g. ChatGPT, Claude) are permitted for brainstorming and editing. All AI use must be disclosed explicitly in the submitted work.

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Heures d'enseignement

  • CMCM24h

Pré-requis obligatoires

Corporate Finance, Financial intermediation, Asset Pricing

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Compétences visées

By the end of the seminar, students will be able to :

  • Critically read and evaluate empirical and theoretical papers at the frontier of financial economics.
  • Analyse the structural forces reshaping credit markets, innovation finance, and sustainable investing.
  • Compare institutional frameworks across regions — particularly the EU vs US financing ecosystems — and assess their economic implications.
  • Synthesise academic evidence and market practice to develop and defend an original research argument.
  • Engage in structured scholarly debate, presenting complex ideas clearly to an expert audience.
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Bibliographie

Session 1 — Private Credit

  • Aramonte, S., Lee, S. & Schrimpf, A. (2023). “Private Credit: Boom and Systemic Risk?” BIS Quarterly Review, September 2023.
  • FSB (2024). Global Monitoring Report on Non-Bank Financial Intermediation. Financial Stability Board.
  • IMF (2024). Global Financial Stability Report, Ch. 2: “The Rise and Risks of Private Credit.” International Monetary Fund.
  • Ivashina, V. & Vallée, B. (2022). “New Private Lenders.” NBER Working Paper No. 30214.


Session 2 — Fintech, Crypto & DeFi

  • Brunnermeier, M., James, H. & Landau, J.-P. (2019). “The Digitalization of Money.” NBER Working Paper No. 26300.
  • Lehar, A. & Parlour, C. (2021). “Decentralized Exchanges.” NBER Working Paper No. 28733.
  • Makarov, I. & Schoar, A. (2022). “Blockchain Analysis of the Bitcoin Market.” Journal of Financial Economics, 150(2), 424–445.
  • BIS (2023). Annual Economic Report 2023, Ch. 3: “Blueprint for the Future Monetary System.”


Session 3 — Sustainable Finance & ESG

  • Bolton, P. & Kacperczyk, M. (2021). “Do Investors Care about Carbon Risk?” Journal of Financial Economics, 142(2), 517–549.
  • Gibson, R., Krueger, P. & Mitali, S. (2022). “ESG Rating Disagreement and Stock Returns.” Financial Analysts Journal, 78(4), 67–94.
  • Hong, H., Li, F. & Xu, J. (2019). “Climate Risks and Market Efficiency.” Journal of Econometrics, 208(1), 265–281.
  • Pedersen, L., Fitzgibbons, S. & Pomorski, L. (2021). “Responsible Investing: The ESG-Efficient Frontier.” Journal of Financial Economics, 142(2), 572–597.


Session 4 — Market Microstructure & Liquidity

  • Budish, E., Cramton, P. & Shim, J. (2015). “The High-Frequency Trading Arms Race.” Quarterly Journal of Economics, 130(4), 1547–1621.
  • O’Hara, M. (2015). “High Frequency Market Microstructure.” Journal of Financial Economics, 116(2), 257–270.
  • Vissing-Jørgensen, A. (2021). “The Treasury Market in Spring 2020.” NBER Working Paper No. 27180.


Session 5 — Innovation Finance: Europe vs US

  • Bats, J. & Houben, A. (2017). “Bank-based versus Market-based Financing: Implications for Systemic Risk.” DNB Working Paper No. 577.
  • Draghi, M. (2024). “The Future of European Competitiveness.” Report for the European Commission, Part B.
  • EIB Group (2024). Investment Report 2023/2024: Retooling Europe’s Economy. European Investment Bank.
  • Hsu, P.-H., Tian, X. & Xu, Y. (2014). “Financial Development and Innovation: Cross-Country Evidence.” Journal of Financial Economics, 112(1), 116–135.
  • Lerner, J. & Nanda, R. (2020). “Venture Capital’s Role in Financing Innovation.” Journal of Economic Perspectives, 34(3), 237–261.
  • Véron, N. & Wolff, G. (2016). “Capital Markets Union: A Vision for the Long Term.” Bruegel Policy Contribution 2016/05.


Session 6 — Private Equity & VC: Value Creation

  • Acharya, V., Gottschalg, O., Hahn, M. & Kehoe, C. (2013). “Corporate Governance and Value Creation: Evidence from Private Equity.” Review of Financial Studies, 26(2), 368–402.
  • Bernstein, S., Giroud, X. & Townsend, R. (2016). “The Impact of Venture Capital Monitoring.” Journal of Finance, 71(4), 1591–1622.
  • Chemmanur, T., Krishnan, K. & Nandy, D. (2011). “How Does Venture Capital Financing Improve Efficiency in Private Firms?” Review of Financial Studies, 24(12), 4037–4090.
  • Gompers, P., Gornall, W., Kaplan, S. & Strebulaev, I. (2020). “How Do Venture Capitalists Make Decisions?” Journal of Financial Economics, 135(1), 169–190.
  • Gornall, W. & Strebulaev, I. (2020). “Squaring Venture Capital Valuations with Reality.” Journal of Financial Economics, 135(1), 120–143.
  • Harris, R., Jenkinson, T. & Kaplan, S. (2014). “Private Equity Performance: What Do We Know?” Journal of Finance, 69(5), 1851–1882.
  • Hellmann, T. & Puri, M. (2002). “Venture Capital and the Professionalisation of Start-Up Firms.” Journal of Finance, 57(1), 169–197.
  • Kaplan, S. & Strömberg, P. (2009). “Leveraged Buyouts and Private Equity.” Journal of Economic Perspectives, 23(1), 121–146.


Session 7 — Macro Finance & Geopolitical Risk

  • Bauer, M. & Swanson, E. (2023). “A Reassessment of Monetary Policy Surprises and High-Frequency Identification.” NBER Macroeconomics Annual, 37, 87–155.
  • di Maggio, M., Franzoni, F., Kacperczyk, M. & Trucchi, S. (2025). “Geopolitical Risk and the Organization of Global Supply Chains.” NBER Working Paper (forthcoming).
  • di Maggio, M. & Kacperczyk, M. (2024). “Financial Markets under Geopolitical Stress.” Working Paper, Harvard Business School.
  • Greenwood, R. & Vayanos, D. (2014). “Bond Supply and Excess Bond Returns.” Review of Financial Studies, 27(3), 663–713.
  • Ilzetzki, E., Reinhart, C. & Rogoff, K. (2019). “Exchange Arrangements Entering the 21st Century.” Quarterly Journal of Economics, 134(2), 599–646.
  • IMF (2024). World Economic Outlook, Ch. 2: “Geoeconomic Fragmentation and Foreign Direct Investment.”


Session 8 — AI & Risk Management

  • Aikman, D., Beale, D., Brinley-Codd, A. & Hüser, A.-C. (2023). “Mapping the Financial System with Network Analysis and Machine Learning.” Bank of England Staff Working Paper.
  • Albanesi, S. & Vamossy, D. (2019). “Predicting Consumer Default: A Deep Learning Approach.” NBER Working Paper No. 26165.
  • Basel Committee on Banking Supervision (2023). Principles for the Effective Management and Supervision of Model Risk from AI/ML. Bank for International Settlements.
  • BIS (2024). “Artificial Intelligence in Central Banking and Financial Stability.” BIS Papers.
  • Flood, M. & Goodhart, C. (2022). “Artificial Intelligence and Systemic Risk.” Journal of Financial Stability, 58, 100906.
  • FSB (2022). “Artificial Intelligence and Machine Learning in Financial Services.” Financial Stability Board Discussion Paper.
  • Fuster, A., Goldsmith-Pinkham, P., Ramadorai, T. & Walther, A. (2022). “Predictably Unequal? The Effects of Machine Learning on Credit Markets.” Journal of Finance, 77(1), 5–47."
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Ressources pédagogiques

Journal articles, online data, policy reports, financial news

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